This application proposes to archive eight waves of data from the Longitudinal Study of Generations and Mental Health (LSOG), a multi-partner, multi-time period study tracing family relationships and well-being through eight waves of data, collected from 1971-2005, from members of three- and four-generation families. The LSOG is one of the longest continuing studies of multi-generational families and mental health in the social and behavioral sciences. One of the unique features of the dataset is its collection of data from several members of the same family. In 2003 the data were archived at the University of Michigan's National Archive for Computerized Data on Aging (NACDA) to make the data more visible to the outside research community. Usage data from NACDA indicates that the LSOG ranks as the 14th most downloaded data set out of the 1,365 data sets archived by NACDA over the last two years and the 6th most popular NIA supported study overall for the same period. We propose to develop user-friendly data extraction protocols and improve the utility of documentation of the study's variables in order to enhance access to and increase use of LSOG data. The proposed activities are justified by the complexity of the data set in terms of time and family configuration, the unrealized potential of the data for scholars seeking to answer research questions with state-of-the-art longitudinal and hierarchical models and methods, and the gap between downloads of the data and what we perceived as its underutilization by the outside (i.e., non-University of Southern California) research community. We propose to work closely with University of Michigan's National Archive for Computerized Data on Aging (NACDA), a repository for data sets that investigate themes of aging, human development, and the life course. NACDA has a long history of working (pro-bono) with outside projects that archive complex data structures. To keep utilization rates at the highest levels, LSOG staff will work with NACDA to configure variable search protocols and case/variable extraction techniques that allow selection of data by topic, time period, and generation, while insuring that family members in five generations can be accurately and conveniently matched with a user- friendly interface. Although the LSOG data set is composed of mostly white subjects, we rely on recognition that the strengths of the data-particularly the long time-horizon and the unique multi-partner analytic designs they allow-compensate for the lack of diversity in the sample, while recognizing that not all users will find their research questions answered here. However, because the LSOG has become the gold standard in measurement of intergenerational relationships, it has been a model for other more diverse data collection efforts. We have continually collaborated with scholars who direct family studies with high representations of minorities in order to validate our measures. PUBLIC HEALTH RELEVANCE: This application requests funds to create tools needed to make the Longitudinal Study of Generations and Mental Health--one of the longest continuing studies of multi-generational families--more accessible to the scholarly community. Activities to make the data more user-friendly include producing more complete and detailed documentation, producing a relational database showing how family members are related to one another over time, and constructing various dyad, triad, and quad family files.